Identification of potential drug targets for rheumatoid arthritis from genetic insights: a Mendelian randomization study

Abstract

Introduction: Rheumatoid arthritis (RA) is a chronic inflammatory illness that mostly affects the joints of the hands and feet and can reduce life expectancy by an average of 3 to 10 years. Although tremendous progress has been achieved in the treatment of RA, a large minority of patients continue to respond poorly to existing medications, owing in part to a lack of appropriate therapeutic targets.

Methods: To find therapeutic targets for RA, a Mendelian randomization (MR) was performed. Cis-expression quantitative trait loci (cis-eQTL, exposure) data were obtained from the eQTLGen Consortium (sample size 31,684). Summary statistics for RA (outcome) were obtained from two largest independent cohorts: sample sizes of 97,173 (22,350 cases and 74,823 controls) and 269,377 (8279 cases and 261,098), respectively. Colocalisation analysis was used to test whether RA risk and gene expression were driven by common SNPs. Drug prediction and molecular docking was further used to validate the medicinal value of drug targets.

Results: Seven drug targets were significant in both cohorts in MR analysis and supported by localization. PheWAS at the gene level showed only ATP2A1 associated with other traits. These genes are strongly associated with immune function in terms of biological significance. Molecular docking showed excellent binding for drugs and proteins with available structural data.

Conclusion: This study identifies seven potential drug targets for RA. Drugs designed to target these genes have a higher chance of success in clinical trials and is expected to help prioritise RA drug development and save on drug development costs.

Keywords: Drug targets; Genetics; Mendelian randomization; Rheumatoid arthritis.

Fig. 1

Overview of the study design

Fig. 2

Manhattan plot of MR analysis in discovery phase. Significant genes were labelled and highlighted in green. The blue line represents the nominal significant threshold of 0.05. The red line represents the Bonferroni correction threshold of 1.96E−5

Fig. 3

Forest plots displaying the findings from the discovery phase for 32 significant genes

Fig. 4

Forest plots displaying the findings from the replication phase for 12 significant genes

Fig. 5

GO enrichment results for three terms

Fig. 6

KEGG enrichment results

Fig. 7

PPI network built with STRING

Fig. 8

PPI network built with GeneMANIA. Each circle is coloured to indicate the functional pathway in which each gene is involved

Fig. 9

Docking results of available proteins small molecules. a FEN1 docking Rhein, b FEN1 docking Tyrphostin AG 538, c FEN1 docking Quercetin, d C5 docking Quercetin, e ATP2A1 docked to Quercetin, f IFNGR2 docked to Quercetin, g HLA-DPA1 docking (–)-isoprenaline